conference · 2014
An Adaptive Step-Size Least Mean Square Algorithm for Electric Power Systems Frequency Estimation in protective relays
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- TL;DR
- This paper introduces a new adaptive step-size Least Mean Square (LMS) algorithm designed to estimate frequencies in electric power systems.
- Problem
- Not specified in the abstract.
- Method
- The approach uses a novel step adaptation method for the LMS algorithm, employing larger step sizes during transients for fast convergence and smaller step sizes in steady-state conditions for high precision.
- Results
- Performance was evaluated using indicators such as mean square error and convergence time across various synthesized and simulated signals affected by noise, harmonics, and voltage and frequency variations.
- Contributions
- Not specified in the abstract.
- Limitations
- Not specified in the abstract.
- Takeaways
- The proposed algorithm is simple, computationally efficient, and capable of signal correction to achieve the desired mean square error.
- Applications
- Electric power systems frequency estimation in protective relays.
- Topics
- Adaptive algorithms, Least Mean Square (LMS), frequency estimation, electric power systems, protective relays
- For industry
- Electric power and energy sector
- Why it matters
- Not specified in the abstract.
Abstract
This paper proposes a new adaptive step-size Least Mean Square Algorithm (LMS) for electric power systems frequency estimation. The algorithm is simple, computationally efficient, and makes the correction of the signal that enables to reach the mean square error. The proposed algorithm has a new kind of step adaption for LMS algorithm that provides high precision in steady state condition using small values of steps, and small time convergence using bigger values in transients. The method's performance was evaluated by indicator such as mean square error and convergence time. The tests were accomplished considering many synthesized and simulated signals with noise, harmonics, voltage and frequency variations.